KT-Biologics I (KTB1): A dynamic simulation model for continuous biologics manufacturing

IF 3.9 2区 工程技术 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Computers & Chemical Engineering Pub Date : 2024-06-14 DOI:10.1016/j.compchemeng.2024.108770
Mohammad Reza Boskabadi, Pedram Ramin, Julian Kager, Gürkan Sin, Seyed Soheil Mansouri
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Abstract

The pharmaceutical industry's shift towards biological therapeutics has led to a transition from conventional batch production to continuous manufacturing. This change highlights the crucial need for effective process monitoring and control strategies to ensure consistent product quality and stability. Open-source benchmark simulation models have become essential tools for refining these processes, offering a platform for testing research hypotheses. This study uses the production of Lovastatin as a case study for continuous biopharmaceutical production. A comprehensive dynamic model covering upstream and downstream components provides an integrated perspective of the production process. The study introduces a basic control system emphasizing realistic sensor and actuator integration to enhance simulation accuracy. It assesses the benchmark through open-loop and closed-loop simulations, offering an in-depth analysis of the KTB1 model's dynamic response and functionality. KTB1 represents a model-driven decision support tool that enables the evaluation of monitoring strategies, process design, process optimization, and control for biomanufacturing.

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KT-Biologics I (KTB1):连续生物制剂生产的动态模拟模型
制药业向生物疗法的转变导致了从传统批量生产向连续生产的过渡。这一转变凸显了对有效工艺监测和控制策略的迫切需要,以确保产品质量和稳定性的一致性。开源基准仿真模型已成为完善这些流程的重要工具,为测试研究假设提供了一个平台。本研究以洛伐他汀的生产作为连续生物制药生产的案例研究。涵盖上游和下游组件的综合动态模型提供了生产过程的综合视角。研究引入了一个基本控制系统,强调传感器和执行器的实际集成,以提高仿真精度。研究通过开环和闭环模拟对基准进行了评估,对 KTB1 模型的动态响应和功能进行了深入分析。KTB1 是一种模型驱动的决策支持工具,可用于评估生物制造的监控策略、流程设计、流程优化和控制。
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来源期刊
Computers & Chemical Engineering
Computers & Chemical Engineering 工程技术-工程:化工
CiteScore
8.70
自引率
14.00%
发文量
374
审稿时长
70 days
期刊介绍: Computers & Chemical Engineering is primarily a journal of record for new developments in the application of computing and systems technology to chemical engineering problems.
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